Although life is based on a fixed genetic blueprint, living systems are dynamic, each developing, surviving, and proliferating in a different way. In responding to change, organisms must themselves change. Signaling, gene activation or suppression, transcription, translation, post-translational modifications, intracellular transport, metabolic processing, and feedback control at the gene, protein, and metabolite level all involve material changes in cells. This almost always occurs through a change in the concentration or flux of cellular components as opposed to changes in their structure. Finding and quantifying these patterns of change is a critical issue in studying regulation and understanding the change that defines biological systems.
Metabolomics is the identification and quantification of all the small molecules present inside or excreted by cells. Although knowledge of the small molecules in cells is a necessary first step in understanding metabolism (Fiehn et al., 2000 Analytical Chemistry 72(15): 3573-80; Roessner et al., 2001 Plant Cell 13(1): 11-29) monitoring changes in their concentration and flux provide deeper insight into cellular physiology.
Major technological advances of the post-genomic era now permit rapid mRNA, protein and ion profiling that are useful in analyzing the proteome and transcriptome. However, the metabolome is unique from the proteome and transcriptome in that it is not directly encoded by the genome. Nonetheless, the ability to quantify and characterize the metabolome is critical for understanding not only role of metabolites in living system but also to elucidate protein function. Transformation of substrate to product is affected either directly though the functional changes of protein or indirectly through protein ability to interact with the other proteins. Likewise, different levels of metabolites can affect the function of other proteins directly by interaction with them or indirectly through changes in physical-chemical conditions inside the cell (low levels of ATP, change in pH etc.). Furthermore, low molecular weight molecules are important components in the communication network among cells, tissues and even whole organisms (e.g. pheromones). Quantification of metabolites is of major importance in elucidating the regulatory impact of metabolites in biological systems (Fiehn et al., Analytical Chemistry 2000, 72:3573-3580). Thus precise quantification of change metabolite concentrations is key element system biology and hold significant promise to identify important relationships between these molecules, proteins and other gene products.
Among the whole cellular metabolic network, central carbon metabolism, which is composed of glycolysis, the pentose-phosphate pathway, and the tricarboxylic acid cycle (TCA), plays a key function in the substrate degradation, energy and cofactor regeneration, and biosynthetic precursor supply. The structure of the metabolic reaction network has been mapped in substantial detail, but comprehensive quantitative analysis of the rates and regulation of cellular metabolic reactions remains a major interest for various biofields, such as enzyme kinetics and enzyme expression patterns (Gancedo and Gancedo, 1973 Biochimie 55(2): 205-11; Entian et al., 1977 Molecular & General Genetics 156(1): 99-105), metabolic engineering (Nielsen, 1998 Biotechnology & Bioengineering 58(2-3): 125-32) and microbial metabolomics (Mashego et al., 2007 Biotechnology Letters 29(1): 1-16). Methodology development to efficiently and accurately measure intracellular intermediate metabolite concentrations under in vivo conditions remains a significant challenge in the study of central carbon metabolism.
There are more than 35 intermediates directly involved in central carbon metabolism, which belong to four categories of chemical compounds: phosphorylated sugars, phospho-carboxylic acids, carboxylic acids, and nucleotides and co-factors. Precise quantification of these intercellular intermediates under in vivo conditions comes with a unique set of challenges from sampling, metabolite extraction, and analytical methods. The intracellular turnover rates for many metabolites are in the range of seconds (De Koning and van Dam, 1992 Anal. Biochem. 204: 118-123), thus, to gain an accurate picture of metabolic concentrations requires a fast sampling and instant deactivation of the enzymatic activity with preservation of cell integrity. Moreover, complete extraction of the metabolites is also essential to reflect in vivo metabolic concentrations. Well-documented methods of sampling, quenching and extraction for yeast are available that comply with these criteria (Gonzalez et al., 1997 Yeast 13(14): 1347-55; Lange et al., 2001 Biotechnology & Bioengineering 75(4): 406-15). The analytical tools for these metabolites have actually existed for several decades; however, analytical methodology has fallen behind the increasing demand from systems biology. Major challenges in the method development arise from the low abundance of most intracellular metabolites, difficulties in distinguishing between metabolites in the same category due to their similarities, and the challenge in developing an effective measurement method due to the diversity between different groups in chemical structure and properties. There appears to be no such available method that could reliably and simultaneously quantify all the intermediates from central carbon metabolism.
Although enzyme-based assays for individually determining certain metabolites have been available for some time (Hajjaj et al., FEMS Microbiol. Lett. 1998, 164:195-200; Ruijter and Visser, J. Microbiol. Methods 1996, 25:295-302; Theobald et al., Biotechnol. Bioeng. 1997, 55:305-316), these assays are time-consuming, and limited to small number of metabolites, depending on the availability of the enzymes. Capillary electrophoresis-mass spectrometry (CE-MS) is a promising tool for ionic metabolites analysis (Soga et al., Anal Chem 2002, 74:2233-2239; Toya et al., J Chromatogr A 2007, 1159:134-141), but generally robustness and sensitivity need to be improved (Cai and Henion, J Chromatogr A 1995, 703:667-692). Currently, liquid chromatography (LC) is a predominant technique for these studies. Due to the anionic property of most metabolites, anion-exchange chromatography (AEC) with UV detection is a commonly used detection method. AEC was first used for the analysis of nucleotides (Cohn, Science 1949, 109:377-378). When the use of AEC was extended to sugar phosphates or carboxylic acids, other detection techniques, such as pulsed amperometric detection (Groussac et al., Enzyme Microb Technol 2000, 26:715-723; Jensen et al., Biotechnol Bioeng 1999, 63:356-362; Smits et al., Anal Biochem 1998, 261:36-42), potentiometric detection (Picioreanu et al., J. Anal Chem 2000, 72:2029-2034) or conductimetric detection (Groussac et al., Enzyme Microb Technol 2000, 26:715-723; Bhattacharya et al., Anal Biochem 1995, 232:98-106; Hull and Montgomery, Anal Biochem 1994, 222:49-54; Ritter et al., J Chromatogr B Analyt Technol Biomed Life Sci 2006, 843:216-226; Vogt et al., Biochem Biophys Res Commun 1998, 248:527-532) were used to circumvent metabolites insufficient UV absorbance, and consequently low UV detection sensitivity.
One of the most common ways of analyzing metabolites is through separation by gas chromatography (GC) or liquid chromatography (LC) followed by identification and quantification through mass spectrometry (MS) (Stephanopoulos et al., Nature Biotechnology 2004, 22:1261-1267; Wamelink et al., J Chromatogr B Analyt Technol Biomed Life Sci 2005:823, 18-25). In the case of a complicated pool of metabolites, one-dimensional LC separation is not sufficient to resolve the multiple metabolites involved. As a powerful detection and quantification tool, mass spectrometry (MS) is also capable of offering a second chance for increased resolution by discriminating molecules based on their m/z values. In addition, tandem MS provides fragmentation information for metabolites structure elucidation and for quantification by selected reaction monitoring (SRM). MS has been widely applied into various LC separation modes for this application. In AEC-MS, due to the high concentration of non-volatile salts in the eluent, which is not acceptable for MS, it was a common practice to mount an after-column desalting device before the eluent enters the MS (van Dam et al., 2002 Anal. Chem. Acta 460: 209-218; Sekiguchi et al., 2005 J Chromatogr A 1085(1): 131-6; Wittmann et al., 2005 Biotechnol Bioeng 89(7): 839-47), which might reduce the separation efficiency. Alternatively, hydrophilic interaction chromatography (HILIC)-tandem MS has been reported to measure large number of cellular metabolites although the analyses were not performed simultaneously (Bajad et al., 2006 J Chromatogr A 1125(1): 76-88).
Among all LC separation modes, reverse phase chromatography (RPLC) is still preferred because of its high separation efficiency, versatility and compatibility with MS. However, in the instance of central carbon intermediates, standard RPLC is ineffectual because these very polar metabolites nearly have no retention on the stationary phases. Although beta-cyclodextrin columns in reverse phase mode (and normal phase mode) have been used for the separation of sugar phosphates, most of the analytes eluted at nearly the dead volume (Feurlea et al., 1998 J Chromatogr A 803: 111-19; Buchholz et al., 2001 Anal Biochem 295(2): 129-37). This situation can be significantly changed by adding ion pairing reagents to the mobile phase, i.e. ion pairing RPLC. This type of reagent should be volatile in compliance with MS detection, such as dimethylhexylamine for nucleotides separation (Tuytten et al., 2002 Rapid Commun Mass Spectrom 16(12): 1205-15; Qian et al., 2004 Anal Biochem 325(1): 77-84), hexylamine for nucleotides, coenzyme A esters, sugar nucleotides, and sugar bisphosphates (Coulier et al., 2006 Anal Chem 78: 6573-82), and octylamine for the separation of pentose phosphate pathway intermediates in blood spots (Finney and Hucka, 2003 Biochem Soc Trans 31(Pt 6): 1472-3; Wamelink et al., 2005 J Chromatogr B Analyt Technol Biomed Life Sci 823(1): 18-25). Oldiges published an ion pairing RPLC-tandem MS method recently, using tributylammonium acetate as an ion paring reagent (Filatov et al., 2007 J Immunological Methods 319(1-2): 21-33). Twenty-three metabolites from central carbon metabolism in the E. coli cell extract were simultaneously detected.
Signal intensity of an analyte in MS depends on its concentration and ionization efficiency. Due to ion suppression these methods have significant problems with precision of quantification. Additionally, ionization efficiency not only varies between analytes but can depend on other components in the matrix, particularly in the case of electrospray ionization (ESI) as used in LC-MS. This problem can theoretically be addressed in LC-MS quantification through the use of a 13C-coded internal standard that co-elutes with the analyte and has an ionization environment identical to the analyte. Synthesizing the requisite 13C-coded internal standard is generally simple when the number of analytes being determined is small. However, when large, the requisite number of syntheses can become prohibitive. Although it is possible to biosynthesize 13C-coded metabolites as was done for D-13C6-glucose 6-phosphate (Huck et al., Clin Chem 2003, 49:1375-1380), and although some 13C-coded metabolites are commercially available, a comprehensive collection of internal standard metabolites is generally not available. Some have used standard addition methods for MS quantification (Huck et al., Clin Chem 2003, 49:1375-1380; Buchholz et al., Anal Biochem 2001, 295:129-137; Luo et al., J Chromatogr A 2007, 1147:153-164; van Dam et al., Anal. Chem. Acta 2002, 460:209-218) to circumvent this problem. However, the MS response can change over time due to changes in the MS instrument (Coulier et al., Anal Chem 2006, 78:6573-6582).
Regnier et al. (U.S. Pat. No. 6,864,099, issued Mar. 8, 2005, and U.S. Pat. No. 6,872,575, issued Mar. 29, 2005) describe a method for mass spectrometric analysis of peptide or protein analytes in a biological sample. The method, referred to as the global internal standard technology (GIST) method, involves differential isotopic labeling of analytes in control and experimental samples such that analytes in the control samples function as internal standards. Metabolites, such as proteins (or peptides if proteolysis is employed) in control and experimental samples are post-synthetically derivatized with chemically equivalent but isotopically distinct forms of a labeling agent, mixed, then subjected to mass spectrometric analysis to determine relative concentrations. The labeling agent is selected so as to react with a particular functional group, such as an amine group or a carboxylic acid, present on the protein or peptide of interest. Labeling reagents useful for labeling amino acids (Yang et al., 2006, Anal. Chem., 78:4702; Regnier et al., PCT Publication WO2007/117665, published Oct. 18, 2007), carboxylic acids (Yang et al., Electrophoresis 2008, 29:4549-4560), estrogen metabolites (Yang et al., 2008 J. Chromatog. B, 870:233-240) and fatty acids (Yang et al., 2007, Anal Chem 79:5150-5157) have also been described. Metabolites, as a general class of compounds, however, have no single, common functional group that can be used for isotope coding. Thus, a number of reagents would be needed in order to achieve truly global internal standard quantification (Yang et al., 2007, Anal Chem 79:5150-5157). Simultaneous analysis of multiple analytes in two or more samples and relative quantification of metabolites by ESI-MS using labeling reagents that are reactive to particular compound classes has been reported by Shortreed et al. (PCT Publication WO2007/109292, published Sep. 27, 2007).